Research on the construction of prediction model for depressive symptom in the second and third trimester of pregnancy based on artificial neural network
Liuyue Wang, Dandan Zhou, Yanhui Liu, Zhiqun Liu, Huan Wan · 2026
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Description
Liuyue Wang and co-authors surveyed in 2026 nearly six hundred pregnant women in two Chinese cities to build a model predicting depressive symptoms late in pregnancy. Participants were in their second or third trimester and attending regular prenatal checkups. Questionnaires covered social support, coping style, personality vulnerability, and parenting confidence alongside a standard depression scale. Two modelling approaches were trained and compared on the same survey data.
More than two fifths of women screened positive for depressive symptoms in the survey. Strong social support and active coping went together with fewer symptoms in the correlations. Negative coping and a vulnerable personality pattern went together with more symptoms in the same analysis. A neural network model predicted symptom status more accurately than a traditional regression model. The authors offer the model to help nurses flag high-risk women early in prenatal care.
Catalog record
| CREATOR | Liuyue Wang, Dandan Zhou, Yanhui Liu, Zhiqun Liu, Huan Wan |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 40 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |